An Integrated Hydrocarbon Biofuel and Petroleum Supply Chain: Designing and Planning a Dynamic Supply Chain Network

One of the main challenges of bioenergy sector development is the cost of biomass supply chain resulted from inefficient bioenergy production from low energy content biomass feedstocks, high logistics costs of biomass production, handling and transportation. Another main aspect to be considered is that the configuration of a biofuel supply chain can be dynamic which evolve over time. Growing demand and increasing of biofuel related incentives, promote considering the assumptions of capacity expansion and evolution in the biofuel production technologies in the existing biofuel supply chains. Accordingly, two approaches are proposed in this research to reduce the mentioned challenges. On the one hand, according to the proposed technology by the U.S. Department of Energy, advanced hydrocarbon biofuel can be achieved by using upgrading units in existing refinery to upgrade biointermediates into final products (e.g. gasoline, diesel and jet fuel) integrated with existing petroleum refineries which can be a good opportunity to use existing infrastructures of petroleum refineries. To be more specific, regarding significant amounts of biorefineries investment costs, taking advantage of refinery units and pipelines leads to saving considerable amounts of investment and annual costs and also achieving more profit from selling new final products. On the other hand, in order to apply dynamic supply chain network design, strategic and tactical time periods are considered, in which the revision of design decisions, such as facilities number, location, and capacity, can occurs at the beginning of each strategic time period. Moreover, in this research, besides of physical flow, optimization of financial flow is considered and maximization of efficiency objective function to optimal design and planning of biofuel supply chain is proposed. In order to investigate the performance of the proposed model a case study is developed for bioethanol supply chain located in Iran and computational results are presented.